Glassnode (On-chain Data) MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Get Bulk Metric, Get Metric, Get Metric Details, and more

Name: Glassnode (On-chain Data)
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Glassnode (On-chain Data) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Glassnode (On-chain Data) MCP Server for LlamaIndex is a standout in the Data Analytics category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Glassnode (On-chain Data). "
            "You have 6 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Glassnode (On-chain Data)?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Glassnode (On-chain Data) MCP Server

Connect your Glassnode account to any AI agent to analyze crypto markets with precision. Fetch real-time and historical on-chain metrics, exchange flows, and network health data through natural conversation.

LlamaIndex agents combine Glassnode (On-chain Data) tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Asset Discovery — List all supported assets and blockchains using list_assets to identify available data points.
Metric Exploration — Query thousands of metric paths with list_metrics and get detailed documentation on parameters via get_metric_details.
Time-Series Analysis — Retrieve historical data for active addresses, exchange balances, and price metrics using get_metric.
Bulk Data — Fetch metrics for multiple assets simultaneously with get_bulk_metric to compare market trends.
Point-in-Time Data — Access immutable historical snapshots via get_pit_metric to eliminate look-ahead bias in backtesting.

The Glassnode (On-chain Data) MCP Server exposes 6 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Glassnode (On-chain Data) tools available for LlamaIndex

When LlamaIndex connects to Glassnode (On-chain Data) through Vinkius, your AI agent gets direct access to every tool listed below — spanning on-chain-data, market-intelligence, crypto-analytics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get bulk metric on Glassnode (On-chain Data)

Use a="*" for all assets. Get bulk metric data for multiple assets

get

Get metric on Glassnode (On-chain Data)

Path should be the metric name like "addresses/active_count" or "market/price_usd_close". Get time-series data for a specific metric

get

Get metric details on Glassnode (On-chain Data)

Get details, allowed parameters, and description for a specific metric

get

Get pit metric on Glassnode (On-chain Data)

Get Point-in-Time (PIT) metric data

list

List assets on Glassnode (On-chain Data)

List all supported assets on Glassnode

list

List metrics on Glassnode (On-chain Data)

Can be filtered by asset, interval, etc. List all available metric paths on Glassnode

Connect Glassnode (On-chain Data) to LlamaIndex via MCP

Follow these steps to wire Glassnode (On-chain Data) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 6 tools from Glassnode (On-chain Data)

Why Use LlamaIndex with the Glassnode (On-chain Data) MCP Server

LlamaIndex provides unique advantages when paired with Glassnode (On-chain Data) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Glassnode (On-chain Data) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Glassnode (On-chain Data) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Glassnode (On-chain Data), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Glassnode (On-chain Data) tools were called, what data was returned, and how it influenced the final answer

Glassnode (On-chain Data) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Glassnode (On-chain Data) MCP Server delivers measurable value.

Hybrid search: combine Glassnode (On-chain Data) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Glassnode (On-chain Data) to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Glassnode (On-chain Data) for fresh data

Analytical workflows: chain Glassnode (On-chain Data) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Glassnode (On-chain Data) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Glassnode (On-chain Data) immediately.

"List all supported assets on Glassnode."

"Get the 'addresses/active_count' metric for BTC from the last 7 days with a 24h interval."

"Show me the details and allowed parameters for the metric path 'market/price_usd_close'."

Troubleshooting Glassnode (On-chain Data) MCP Server with LlamaIndex

Common issues when connecting Glassnode (On-chain Data) to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Glassnode (On-chain Data) + LlamaIndex FAQ

Common questions about integrating Glassnode (On-chain Data) MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Glassnode (On-chain Data) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.